Continuous advances in wearables, sensors and smart Wireless Body Area Network technologies have precipitated the development of new applications for on-, in- and body-to-body wearable communications for healthcare and sport monitoring. Progress in this cross-disciplinary field is further influenced by developments in radio communication, protocols, synchronization aspects, energy harvesting and storage solutions, and efficient processing techniques for smart antennas. This book covers various scenarios and solutions using sensor devices and systems for activity recognition and their applications, including wearable communication, smart sensing, RF propagation, and measurement. The authors illustrate conceptual aspects and applications, and provide a new vision in characterising wearable technologies and the need for interoperability. Energy harvesting within wearable solutions is a key issue addressed here as it helps increase energy efficiency and reliability in wearable antennas and sensor devices.
Inspec keywords: gait analysis; wireless sensor networks; wearable antennas; Zigbee; body area networks; energy harvesting; biomedical telemetry; obstetrics
Other keywords: energy harvesting; healthcare; hardware-efficient time synchronization; foetal movement monitoring; supercapacitor radio frequency energy harvesting; medical WBANs; cognitive radio; -movement identification; wireless body sensor networks; packet concatenation; human gait analysis; first response team body-area environment monitoring; wearable technologies; high data rate; human activity recognition systems; sub-layer protocols; textile material electromagnetic characterisation; RF energy harvesting; multichannel scheduled channel polling
Subjects: Antennas; Biomedical communication; Telemetry; Patient diagnostic methods and instrumentation; Wireless sensor networks; General electrical engineering topics; Physics of body movements; Microwaves and other electromagnetic waves (biomedical imaging/measurement); Sensing devices and transducers; Textbooks; Microwaves and other electromagnetic waves (medical uses)
The new book Wearable Technologies and Wireless Body Sensor Networks for Healthcare is included in the Healthcare Technologies series from IET. This specific book is dedicated to topics that span from scenarios and WSBN communication-applications to sensor devices and systems, activity recognition, monitoring of the human gait through the application of dedicated IC, smart textiles and their applications to smart sensing, RF propagation aspects, detailed modelling of this very complex communication environments, measurements and CR, link layer, MAC sub-layer protocols and synchronization aspects, aspects of network layer, the medical applications of WBSNs as well as the underlying wearable solutions.
The tremendous advances in radio communications and ultra-low power (ULP) electronics have enabled the development of communicating biomedical sensors for the continuous monitoring of patients' physiological signals. In the last decade, much research has been done towards the advancement of wireless body area network (WBAN) technology, resulting in the release of the IEEE 802.15.6-2012 standard for the interconnection of wearable and implantable biomedical sensors. This chapter provides an overview of the sets of wireless body sensor network (WBSN) applications, as well as of their characterization parameters. One of the key requirements for widespread adoption of the WBSN technology for daily healthcare is, however, the ease of use of the sensing devices. From the patient's perspective, this means that besides being small, unobtrusive and ergonomic, WBAN nodes have to be capable of long-term operation without the need to frequently charge, recharge or even use batteries. Although the recent advances in ULP electronics have reduced the power consumption of major WBSN node components to the sub-milliwatt (sub-mW) level, the vision for uninterrupted self-powered WBANs has yet to be realized. Energy harvesting (EH), i.e. taking energy from ambient sources to power autonomous wireless networked systems, is a developing technology with a tremendous potential to complement ULP electronics towards the realization of this vision, thereby enabling the perpetual remote monitoring of a patient's vital signs. An integrated circuit (IC) that integrates most of network functionalities onto low power wearable systems has been introduced as well.
This chapter addresses a wearable body area network (BAN) system for both medical and nonmedical applications, especially those including a large number of sensors at BAN scale (<250), embedded in textile and with high data rate (<9+9 MHz) communication demands. The overall system includes an on-body central processing module (CPM) connected to a computer via a wireless link and a wearable sensor network. Due to the fixed location of the sensors and the possibility of using conductive yarns in textiles, a wired network has been considered for the wearable components. Employing conductive yarns instead of using wireless links provides a more reliable communication, higher data rates and throughput, and less power consumption. The wearable unit is composed of two types of circuits, the sensor nodes (SNs) and a base station (BS), all connected to each other with conductive yarns forming a mesh topology with the base node at the center. The reliability analysis shows that communication in a multi-hop connection of sensors in mesh topology is more reliable than in the conventional star topology. From the standpoint of the network, each SN is a four port router capable of handling packets from destination nodes to the BS. The end-to-end communication uses packet switching for packet delivery from SNs to the BS or in the reverse direction, or between SNs. The communication module has been implemented in a low power field programmable gate arrays (FPGA) and a microcontroller. The maximum data rate of the system is 9+9 Mbps while supporting tens of sensors, which is much more than current BAN applications need. The suitability of the proposed system for utilization in real applications has been demonstrated experimentally.
This chapter addresses a number of activity recognition methods for a wearable sensor system. Three methods for data transmission, namely `stream-based', `feature-based' and `threshold-based' scenarios are applied to study the accuracy against energy efficiency of transmission and processing power that affects the mote's battery lifetime. The impact of variation of sampling frequency and data transmission rate on energy consumption of motes is also analysed for each method. This study leads the authors to propose a cross-layer optimisation of an activity recognition system for provisioning acceptable levels of accuracy and energy efficiency.
The accurate characterisation of textile materials to be used as a dielectric substrate in wearable systems is fundamental. However, little information can be found on the electromagnetic properties of regular textiles. Woven, knits and non-wovens are inhomogeneous, highly porous, compressible and easily influenced by the environmental hygrometric conditions, making their electromagnetic characterisation difficult. For these reasons, there is no standard method to measure the dielectric properties of textiles. This chapter presents a survey on the evolution of flexible antennas and the textile materials used to manufacture them. Besides, it gives an overview of several methods used to characterise the permittivity of textile materials. Furthermore, it presents and applies a resonator-based experimental technique to characterise textile materials. This experimental technique is based on the theory of resonant methods and consists in calculating the electromagnetic parameters of the material under test (MUT), at a single frequency, by measuring the shift in frequency and the value of Q-factor of one resonator board with a microstrip patch antenna. To validate the experimental characterisation method, four textile antennas have been designed to resonate in the 2.45 GHz ISM band. This bandwidth (BW) also supports the Wireless Local Area Network (WLAN), Bluetooth and Short Range Communication Systems (SRCS) applications. All antennas operated in the targeted frequency band and showed excellent agreement between simulated and measured parameters, supporting the validation of this method. The resonator-based experimental technique proved to be an efficient, simple, easy and fast technique for the characterisation of electromagnetic propertiesof textile materials for the development of wearable antennas and body-centric communication.
In this chapter, an intensive study of a novel human movement identification scheme using the radio signal strength in wireless body area network (WBAN) is presented. Since the WBAN channel characteristics are highly influenced by the human movement, the radio signal strength and its temporal variation can be used to determine the human movement without additional tools such as an accelerometer/gyroscope. This study included the process of developing the human movement identification system, performance assessment on different conditions including a vector size of the received signal levels, an antenna orientation, a classifier training algorithm, and a receiver location. It was found that the vector size of the received signal levels and the receiver location had strong impact on the identification accuracy. More than 80% of the identification accuracy can be achieved when using 30-40 received signal levels or the receiver location at thigh or upper arm. In addition, a feature selection method based on a correlation coefficient was used to remove redundant and less informative features. The classification results show that the comparable performance to the all feature vectors can be achieved by the subset feature vector with a lower computational cost.
Wearable wireless medical sensors beneficially impact the healthcare sector, and this market is experiencing rapid growth. Globally, the digital health market is forecast to increase from $80 billion in 2015 to $200 billion in 2020. Medical body area networks (MBANs) improve the mobility of patients and medical personnel during surgery, accelerate the patients' recovery, while facilitating the remote monitoring of patients suffering from chronic diseases. Currently, MBANs are being introduced in unlicensed frequency bands, where the risk of mutual interference with other electronic devices can be high. Techniques developed during the evolution of cognitive radio (CR) can potentially alleviate these problems in medical communication environments. In addition, these techniques can help increase the efficiency of spectrum usage to accommodate the rapidly growing demand for wireless MBAN solutions and enhance coexistence with other collocated wireless systems. A viable architecture of an MBAN with practical CR features is proposed in this work. Additionally, ultra wideband (UWB) radio for the implementation of CR offers many advantages to MBANs, and some features of this technology can be exploited for effective implementation of CR. Conceptual aspects associated with energy harvesting and practical identification of spectrum opportunities for radio frequency (RF) energy scavenging motivates the options taken in the development of the protocols. The physical (PHY) and medium access control (MAC) layer aspects of the proposal are proposed in addition to their implementation challenges in the context of CR.
This chapter proposes an IEEE 802.15.4 medium access control (MAC) sub-layer performance enhancement by employing request-to-send/clear-to-send (RTS/CTS) combined with packet concatenation. The results have shown that the use of the RTS/CTS mechanism improves channel efficiency by decreasing the deferral time before transmitting a data packet. In addition, the sensor block acknowledgement (ACK) (BACK) MAC (SBACK-MAC) protocol has been proposed that allows the aggregation of several ACK responses in one special BACK response packet. Two different solutions are briefly considered. The first one considers the SBACK-MAC protocol in the presence of BACK request (concatenation) while the second one considers the SBACK-MAC in the absence of BACK request (piggyback). The throughput and delay performance is mathematically derived under both ideal conditions (a channel environment with no transmission errors) and nonideal conditions (a channel environment with transmission errors). An analytical model is proposed, capable of taking into account the retransmission (RTX) delays and the maximum number of backoff stages. The simulation results successfully validate analytical model. Besides, an innovative efficient multichannel MAC (McMAC) protocol, based on SCP-MAC, has also been proposed, the so-called multichannel scheduled channel polling MAC (MC-SCP-MAC) protocol. The influential range (IR) concept, denial channel list (which considers the degradation metric of each slot channel), extra resolution (ER) phase algorithm and frame capture effect are explored to achieve the maximum performance in terms of delivery ratio and energy consumption. It is shown that MC-SCP-MAC outperforms SCP-MAC and multichannel lightweight medium access control (MC-LMAC) in denser scenarios, with improved throughput fairness. Considering theIR concept reduces the redundancy level in the network facilitating to reduce the energy consumption whilst decreasing the latency. The conclusions from this research reveal the importance of an appropriate design for the MAC protocol for the desired wireless body sensor network (WBSN) application.
This chapter presents a one-way method for synchronization at the media access control (MAC) layer of nodes and a circuit based on that in a wearable sensor network. The proposed approach minimizes the time skew with an accuracy of half of clock cycle in average. The work is intended to be used in a router integrated circuit (IC) designed for wearable systems. In particular, we address the need for good time synchronization in the simultaneous acquisition of surface electromyographic signals of several muscles. In our main application case, the electrodes are embedded in patient clothes connected to sensor nodes (SNs) equipped with analog-to-digital converters. The SNs are connected together in a network using conducting yarns embedded in the clothes. In the context of such wearable sensor networks, the main contributions of this work are the evaluation of existing protocols for synchronization, the description of a simpler, resource-efficient synchronization protocol, and its analysis, including the determination of the average local and global clock skew and of the synchronization probability in the presence of link failures. Both theoretical analysis and experimental results, in wired wearable networks, show that the proposed protocol has a better performance than precision time protocol (PTP), a standard timing protocol for both single and multihop situations. The proposed approach is simpler, requires no calculations, and exchanges fewer messages. Experimental results obtained with an implementation of the protocol in 0.35 μm complementary metal oxide semiconductor (CMOS) technology show that this approach keeps the one-hop average clock skew around 4.6 ns and peak-to-peak skew around 50 ns for a system clock frequency of 20 MHz.
A new wearable data capture system for gait analysis is being developed. It consists of a pantyhose with embedded conductive yarns interconnecting customized sensing electronic devices that capture inertial and electromyographic signals and send aggregated information to a personal computer through a wireless link. The use of conductive yarns to build the myoelectric electrodes and the interconnections of the wired sensors network as well as the topology and functionality of the sensor modules are presented.
E-health environments are extremely complex and challenging to manage, as they are required to cope with an assortment of patient conditions under various circumstances with a number of resource constraints. E-health devices usually indicate a piece of equipment with the mandatory capabilities of communication and some optional capabilities of sensing, actuation, data capture, data storage and data processing. The devices would collect various kinds of information and provide it to the information and communication networks for further processing and would operate in a dynamic environment, which would require unobtrusive monitoring and interacting with the inhabitants (i.e., patients) while they perform their activities of daily living (ADL). The devices should be able to recognise abnormal events as well as slowly emerging shifts in behaviour, and able to inform associated users (caregivers, healthcare professionals, family) appropriately and timely, in order to provide a feeling of safety and comfort for all involved parties. This chapter describes an e-Health Home Caring Environment designed to cater to patients with Mild Cognitive Impairments (MCI), Chronic Obstructive Pulmonary Disease (COPD) and seniors with frailty conditions. It details the required software and hardware technological innovations to design an affordable, easy-to-install smart “caring home” cognitive environment, which “senses” intuitively the wishes and “learns” the needs of the person living in the home. As a result, the environment provides unobtrusive daily support, notifying informal and formal caregivers when necessary and serving as a bridge to supportive services offered by the outside world.
Under the VitalResponder® (VR) line of research, mostly funded by the Carnegie Mellon University (CMU)-Portugal program, we have been developing, in partnership with colleagues from CMU, novel wearable monitoring solutions for hazardous professionals such as first responders (FR). We are exploring the synergy between innovative wearable technologies, scattered sensor network and precise localization to provide secure, reliable and effective first-response information services in emergency scenarios. This enables a thorough teams'management, namely on FR exposure to different hazardous elements, effort levels and critical situations that contribute to team members' stress and fatigue levels.
There is no doubt about the interest of evaluating foetal health through its movements' profile, mainly by counting them at determined intervals. Presently, this is only available through mother's intervention, which is, naturally, extremely sensitive to subjective interference, like anxiety. To turn this method more efficient and comfortable a wearable autonomous device is desirable, both for its expected accuracy in identifying their number and also their type and allowing a prolonged observation. The aim of our research project “Smart-Clothing” has been to find adequate sensors to identify the various foetal movement types (full body, head or limb extension and flexion, respiratory) and to apply them to abdominal belt, tape or girdle, to be continuously used by pregnant women, mainly during the day, but even at night. Although the resulting prototypes have not been considered to fulfil the requirements previously defined, the work done and the performed experiences had given useful information for further developments. A few years after the end of that project, the description of the trials and results obtained seem to be useful data to serve as a basis for the design of future projects.
The radio frequency energy harvesting (RF-EH) and storing solution proposed in this chapter allows for collecting only a small amount of energy. However, it is more stable than solar and wind power sources. In fact, RF-EH relies on ambient RF signals from communications systems; hence, it presents special characteristics not found in other types of energy sources. The amount of RF energy harvested depends on the schedules of the base stations from the telecommunication service, as well as on the fluctuations caused by multipath fading and shadowing. As such, this work introduces a novel energy-management algorithm whilst proposing a supercapacitor storing system that copes with these issues and allows for storing the energy harvested from the electromagnetic waves by means of N-stage Dickson voltage multiplier printed circuit board (PCB) boards (5 and 7 stages) optimized to guarantee the best conversion efficiency and output voltage. Since the objective is to harvest as much energy as possible from the electromagnetic spectrum, this work proposes an RF-EH prototype to harvest electromagnetic energy from the digital terrestrial television (DTT) frequency band (750-758 MHz). This band is chosen due to the potential arising from the wide/broad deployment of DTT in Portugal, which poses significant interest for EH. Regarding the supercapacitor storing system, the best electronic components as well as the most suitable values for the configuration parameters have been determined through an empirical approach for the RF-EH with supercapacitor storing system. As an ongoing work, we are addressing the possibility of using different RF-EH prototypes gathered in blocks that scavenge energy in the same or different frequency bands, where the sum of all the energy harvested from each prototype is stored in the supercapacitor-based storage system, is also being considered. Preliminary tests are very promising, as in a conference room, densely populated, with circa 300 people, the RF-EH system managed to build up and store energy even when mobile phones were not being used in the close proximity of the harvesting antennas.
This chapter not only gives a final overview of the main topics covered in the book but also presents a taxonomy for the classification of wearable devices that was proposed, and the literature review identified papers whose authors applied SWOT analysis to this market by examining their strengths, weaknesses, opportunities and some of the major threats they face. Such work gives insights on the primary areas of innovation in wearable healthcare, which include infant safety and care, elderly care, chronic disease management, military support, sports medicine and preventive medicine.This is certainly vital to the widespread implementation and success of the wearable healthcare technology, as it is an important step towards enhancing the interaction of wireless body-area networks (BANs) (WBANs) with traditional healthcare databases and electronic health record (EHR) systems.
